Method and apparatus for providing congestion management for a wireless communication network

ABSTRACT

A method and apparatus for providing a congestion management of a wireless communication network are disclosed. For example, the method projects dynamically a trend for a network element of the wireless communication network, using a functionality metric associated with the network element of the wireless communication network, and determines if there is a potential congestion in accordance with the trend. The method then provides a notification of the potential congestion, if there is a potential congestion for the network element of the wireless communication network.

This application is a continuation of U.S. patent application Ser. No.15/131,895, filed Apr. 18, 2016, now U.S. Pat. No. 9,699,089, which is acontinuation of U.S. patent application Ser. No. 14/577,668, filed Dec.19, 2014, now U.S. Pat. No. 9,319,932, which is a continuation of U.S.patent application Ser. No. 13/151,154, filed Jun. 1, 2011, now U.S.Pat. No. 8,953,443, all of which are herein incorporated by reference intheir entirety.

The present disclosure relates generally to communication network and,more particularly, to a method and apparatus for providing congestionmanagement for a wireless network, e.g., a Long Term Evolution (LTE)network.

BACKGROUND

As usage of mobile user endpoint devices continues to grow, the wirelessnetworks are supporting an ever increasing amount of traffic to and fromthe mobile user endpoint devices. For example, service providers areimplementing Third Generation Partnership Project (3GPP) Long TermEvolution (LTE) networks to support the ever increasing traffic. When anLTE network experiences congestion, a large number of customers will beaffected. One approach to reduce the effect on customers is to designthe LTE network for a worst case scenario. Unfortunately, designing forthe worst case scenario reduces the efficiency of the utilization of thevarious network resources given that the worst case scenario may notoccur on a regular basis. In addition, the design based on a worst casescenario may be cost prohibitive.

SUMMARY

In one embodiment, the present method and apparatus provide a congestionmanagement of a wireless communication network. For example, the methodprojects dynamically a trend for a network element of the wirelesscommunication network, using a functionality metric associated with thenetwork element of the wireless communication network, and determines ifthere is a potential congestion in accordance with the trend. The methodthen provides a notification of the potential congestion, if there is apotential congestion for the network element of the wirelesscommunication network.

BRIEF DESCRIPTION OF THE DRAWINGS

The teaching of the present disclosure can be readily understood byconsidering the following detailed description in conjunction with theaccompanying drawings, in which:

FIG. 1 (shown as FIG. 1A and FIG. 1B) illustrates an illustrative LTEnetwork related to the present disclosure;

FIG. 2 illustrates a flow chart of a method for providing congestionmanagement for an LTE network of the present disclosure;

FIG. 3 illustrates a flow chart of a method for providing a congestioncontrol by directing traffic to a secondary virtual local area network(VLAN);

FIG. 4 illustrates a flow chart of a method for providing a congestioncontrol for controlling traffic; and

FIG. 5 illustrates a high level block diagram of a general purposecomputer suitable for use in performing the functions described herein.

To facilitate understanding, identical reference numerals have beenused, where possible, to designate identical elements that are common tothe figures.

DETAILED DESCRIPTION

The present disclosure broadly describes a method and apparatus forproviding congestion management for a wireless network, e.g., a LongTerm Evolution (LTE) network. Although the teachings of the presentdisclosure are discussed below in the context of LTE networks, theteaching is not so limited. Namely, the teachings of the presentdisclosure can be applied for other types of wireless networks inaccordance with other standards, e.g., 2G networks, 3G networks, etc.

In a 3GPP Long Term Evolution (LTE) network, congestion may occur for avariety of reasons. For example, the network may be congested due tointroduction of applications that require large bandwidth, introductionof applications that generate bursty traffic, occurrence of networkevents (e.g., network failures), increase in a number of long distancehigh speed connections, and so on.

The network congestion may affect the quality of service. One approachto reduce network congestion is to design the network for a worst casescenario. Unfortunately, designing for the worst case scenario reducesthe efficiency of the utilization of the various network resources.Furthermore, designing for a worst case scenario is very costly to aservice provider of the LTE network.

To address this criticality, the present method and apparatus providecongestion detection and control capabilities that enable higherengineered loads in the network. In one embodiment, the congestiondetection and control capabilities provide adaptive congestion detectionand control for Virtual Local Area Networks (VLANs) in the LTE network.

Broadly defined, an eNodeB is a radio base transceiver station (RBS) asper the 3GPP standards (or simply referred to as a base station). AneNodeB provides the LTE air interface and performs radio resourcemanagement for wireless access. 3GPP is a global effort to define awireless communication system specification. In 3GPP release 8, LTE is aset of enhancements to the Universal Mobile Telecommunications System(UMTS) which focuses on adopting 4th Generation (4G) mobilecommunications technology, including an all Internet Protocol (IP)end-to-end networking architecture.

FIG. 1 illustrates an exemplary LTE network 100 related to the presentdisclosure. In one illustrative embodiment, the LTE network 100comprises an access network 102 (e.g., an evolved Universal TerrestrialRadio Access Network (eUTRAN)), a backhaul network 109, a core network103 (e.g., an Evolved Packet Core (EPC) network), and a congestioncontrol system 104, e.g., supported and operated by a wireless serviceprovider. It should be noted that congestion control system 104 can bedeployed in any of the network illustrated in FIG. 1. Furthermore,although various networks are shown as separate networks in FIG. 1, itis possible that functions performed by these networks can be combinedinto fewer networks or expanded into a greater number of networksdepending on the deployment requirements.

In one illustrative example, the eUTRAN, e.g., eUTRAN 102, may compriseone or more eNodeBs, e.g., 111 and 112. In operation, user equipment oruser endpoint (UE) 101 may access wireless services via an eNodeB, e.g.,eNodeB 111 or eNodeB 112 in the eUTRAN 102. UE 101 can be a smart phone,a cellular phone, a computer or laptop, or any endpoint communicationdevices equipped with wireless capabilities. An eNodeB, such as eNodeB111 or 112, provides wireless interfaces to one or more UE devices. AlleNodeBs in the eUTRAN 102 are connected to the EPC network 103 via oneor more integrated access devices 105 (e.g., a Smart Integrated AccessDevice (SIAD)) located in backhaul network 109. Broadly, an integratedaccess device is capable of integrating both voice and data serviceswithin a single device. In one embodiment, eNodeB 111 supports wirelessservices covered by cell site 121, and eNodeB 112 supports wirelessservices covered by cell site 122. It should be noted that any number ofeNodeBs can be deployed.

In one embodiment, eUTRAN 102 is connected to the EPC network 103 viathe backhaul network 109. For example, SIAD 105 in the backhaul network109 is connected to the EPC network 103 via a Multi-service Node (MSN)106. An EPC network provides various functions that support wirelessservices in the LTE environment. In one embodiment, an EPC network is anInternet Protocol (IP) packet core network that supports both real-timeand non-real-time service delivery across a LTE network, e.g., asspecified by the 3GPP standards.

In one embodiment, the SIAD is a device that provides wireless trafficaggregation and backhaul from a cell site to an EPC network. An MSNprovides layer 2 and layer 3 networking functions for wireless servicebetween one or more SIADs and the EPC network. The eUTRAN 102 is the airinterface of the 3GPP's Long Term Evolution (LTE) specifications formobile networks. Namely, the eUTRAN comprises a radio access networkstandard that will replace previous generations of air interfacestandards.

In one embodiment, the SIAD 105 and the MSN 106 communicate over abackhaul network 109. The backhaul network may also be referred to as ametro Ethernet transport network. In one embodiment, the backhaul maycomprise a plurality of paths, e.g., a primary path and a secondary pathfrom the SIAD to the MSN. For example, two VLANs may be configuredbetween the SIAD 105 and MSN 106. Under normal conditions, the primaryVLAN is used. When a network condition occurs, e.g., a scheduled outage,a failure, etc., that affects the primary VLAN, traffic can be partiallyor wholly re-directed to the secondary VLAN as discussed further below.In another example, the primary and secondary VLANs may be provided overtwo different SIADs and two different MSNs.

In EPC network 103, network devices Mobility Management Entity (MME) 107and Serving Gateway (SGW) 108 support various functions as part of theLTE network 100. For example, MME 107 is the control node for the LTEaccess-network. In one embodiment, it is responsible for UE (UserEquipment) tracking and paging (e.g., such as retransmissions), beareractivation and deactivation process, selection of the SGW, andauthentication of a user. In one embodiment, SGW 108 routes and forwardsuser data packets, while also acting as the mobility anchor for the userplane during inter-eNodeB handovers and as the anchor for mobilitybetween LTE and other wireless technologies, such as 2G and 3G wirelessnetworks.

In addition, EPC (common backbone) network 103 may comprise a HomeSubscriber Server (HSS) 191 that contains subscription-relatedinformation (e.g., subscriber profiles), performs authentication andauthorization of a wireless service user, and provides information aboutthe subscriber's location. The EPC network 103 may also comprise aPolicy Charging and Rule Function (PCRF) 192 that supports accesses tosubscriber databases and specialized functions of a charging system. TheEPC network 103 may also comprise a Public Data Network Gateway (PDN GW)193 which serves as a gateway that provides access between the EPCnetwork 103 and various data networks, e.g., other IP networks, trustedor non-trusted networks 194-196 and the like. It should be noted thatthe above illustrated LTE network 100 is only illustrative and thenumber of network components or elements are not specifically limited asshown. Any number of network components or elements can be deployed.

In one embodiment, the congestion control system 104 comprises acollection of modules that provides congestion detection and controlcapabilities to address congestions that may occur in the LTE networkfrom time to time. For example, the congestion control system 104 maycomprise a network monitoring module 131, a rule management module 132,a trouble reporting module 133, a service optimization module 134, andan inventory database 135. The functions performed by these modules willbe described below. It should be noted that these various modules mayperform other functions. Only the functions relates to the presentdisclosure are herein described. Furthermore, although these modules areillustrated as separate modules, the functions performed by thesemodules can be implemented in one or more hardware systems, e.g.,application servers and the like.

In one embodiment, the network monitoring module 131 is able to predictand identify potential congestions and to notify the rule managementmodule 132. In turn, the rule management module is able to performtrouble isolation and root-cause analysis. If the rule management moduledetermines that the trouble is specifically due to congestion, and thecongestion is due to an increase in usage of applications that generatebursty traffic or an increase in the number of applications and/or theirrespective bandwidth requirements, the rule management module may send acongestion alarm to the service optimization module 134. In oneembodiment, the service optimization module 134 may check to determineif monitored traffic data for a particular VLAN has risen to such anextent that it has reached or crossed one or more thresholds forcongestion. When needed, i.e., the existence of congestion, the serviceoptimization module may redirect newly arriving lower priority trafficto one or more backup VLANs.

In one embodiment, when congestion has been verified for a VLAN, e.g., aprimary VLAN, the service optimization module may direct newly arrivingtraffic to another VLAN that serves as a backup VLAN for the congestedVLAN. In one embodiment, the service optimization module redirects newlyarriving lower priority traffic to a backup VLAN while continuing toserve newly arriving higher priority traffic on the primary VLAN. In oneembodiment, the service optimization module enables newly arrivinghigher priority traffic to preempt lower priority traffic that isalready being served by the primary VLAN. In one embodiment, thepreempted lower priority traffic may be redirected to the backup VLAN.

In one embodiment, the inventory database 135 contains the inventory ofall network topologies, VLAN configurations, interface configurationsand other network data of the LTE network 100. In one embodiment, thetrouble reporting module 133 communicates with the rule managementmodule 132 and reports troubles to a work center 136.

In one embodiment, the eUTRAN network 102, the backhaul network 109 andthe EPC network 103 include various data bearer paths and signalingbearer paths. The various bearer paths may be referred to by specificlabels. For example, the data bearer path on line 152 may be referred toas an S1-U bearer path and the data bearer path on line 153 may bereferred to as an S5 or an S8 bearer path. In another example, thesignaling bearer path between the eUTRAN and the MME 107 may be referredto as an S1-MME bearer path. Note that the S1, S5, S8, Gx and X2interfaces are standard interfaces defined by the 3GPP standard. Itshould be noted that the present disclosure is not limited to thesespecific interfaces.

Shown illustratively in FIG. 1, the X2 interface flow 151 is used toprovide communication between two eNodeBs, e.g., between eNodeB 111 andeNodeB 112 within the eUTRAN network. The S1 interface flow 152 is usedto provide communication between an eNodeB, such as eNodeB 111, and adevice in the EPC network 103, such as MME 107 and/or SGW 108. The Gxinterface flow 154 is used to provide communication between the PGW 193(also referred to as PDN GW 193) and the PCRF 192. The S5 interface flow153 is used to provide communication between the SGW 108 and PDN GW 193.

In one embodiment, the current method performs an adaptive congestiondetection and control by first gathering performance management data foreach physical and logical port in the LTE network, e.g., LTE network100. For example, the performance management data may be gathered by anetwork monitoring module on a per VLAN and/or per network interfacebasis. For example, for the LTE network 100, the performance monitoringdata may be gathered for each VLAN to eNodeB physical interface, SIAD toMSN physical interface, logical interfaces between the various networkelements of the LTE network (e.g., SGW, PGW, PCRF, MME, HSS, etc.). Forexample, various physical interfaces can be supported by a VLAN inaccordance with a VLAN assignment. Furthermore, multiple VLANs may alsobe supported by the same physical interface.

It should be noted that the network elements of the EPC network haveexternal and internal VLANs. The internal VLANs may be used to supportlogical interfaces among the various elements of the EPC network, e.g.,among PCEFs (policy and charging enforcements), SGWs and PGWs. TheExternal VLANs may be used to support logical interfaces forcommunicating with other network elements of the LTE network (e.g., toeUTRAN network elements, to other packet networks, etc.).

Table 1 provides an illustrative table for VLAN identificationassignments for an interface between an eNodeB to a SIAD. For example,the VLAN identification assignments may be for an interface between aneNodeB 111 or eNodeB 112 and the SIAD 105. Table 2 provides anillustrative VLAN identification assignment table for an interfacebetween a SIAD and an MSN. For example, the interface may be between theSIAD 105 and the MSN 106. Tables 3 and 4 provide an illustrative logicalinterface to external VLAN assignment table and an illustrative logicalinterface to internal VLAN assignment table, respectively. It should benoted that these tables are only illustrative and are provided to assistin the understanding of the present disclosure.

TABLE 1 VLAN ID assignment for an interface between an eNodeB and aSIAD. Traffic Type Bearer OAM Point-to-Point Equipment Type VLAN VLANVLAN LTE BBU-1 212 211 213 eNodeB-1 BBU-2 215 214 216 UMTS NodeB-1 101102 103 UMTS NodeB-2 104 105 106

TABLE 2 VLAN ID assignment for an interface between a SIAD and an MSN.Secondary MSN Number SIAD Number Primary MSN Number (If applicable) SIAD1 1000 2000 SIAD 2 1001 2001 . . . . . . . . . SIAD 1000 1999 2999 . . .. . . . . . SIAD 1200 3199 3699

TABLE 3 Logical interface to external VLAN assignment. External VLANsSupported by Interface VLAN Number Gn, S5, S1-U, S11 402 SGi 400 Gx, Gy,Gz 401

TABLE 4 Logical interface to internal VLAN assignment. Internal VLANsSGW PGW PCEF S1-U, S11, S5 2403 Gn, S5 2402 PGW to PCEF-c 1110, 1210,1310 1110, 1210, 1310 PGW to PCEF-u 2110, 2210, 2310 2110, 2210, 2310SGi 2400 Gx 2600 Gy, Gz 2700 2700 OAM 2001 2001 2001

In one embodiment, the utilization can be tracked for each physicalinterface or port, for each logical interface or port, and for each VLAN(each broadly referred to as a network element). For example, thenetwork monitoring module may track various interface utilizations todetect a potential congestion for a particular interface and/or a VLANby monitoring traffic associated the following entities or parameters:

-   -   Diameter Credit Control Application (DCCA);    -   Access Point Names (APNs);    -   Charging Gateway (CG);    -   GPRS Tunnel Protocol (GTP);    -   Persistent Storage Device (PSD);    -   PDP Contexts;    -   Server Load Balancing (SLB);    -   IP Traffic Thresholds; and    -   Quality of Service (QoS).

In one embodiment, the data to be used by the network monitoring moduleis gathered using probes. For example, diagnostic probes may be placedon Ethernet links, ports, interfaces, etc.

In one embodiment, the performance data to be collected by the networkmonitoring module depends on the entity or parameter being monitored.For example, the type of data to be monitored at a network elementlevel, at a card level, at a port level, at a VLAN level, at a physicalinterface level, at a logical interface level, and so on may bedifferent.

In one embodiment, the performance management data to be gathered isselected by the network service provider. For example, if the networkservice provider considers a particular type of data as being a keyindicator for congestion detection of a VLAN, the network serviceprovider may monitor the particular type of data for various VLANs.

Table-5 provides an illustrative set of performance data to be collectedby the network monitoring module.

Level Performance Data Network Device uptime element Device memoryutilization (e.g., per 5 minute intervals) level Device CPU utilization(e.g., per 5 minute intervals) Packets (e.g., OctetsReceived/Transmitted) Device discards/errors (totals and percentages)Card level Device uptime Device memory utilization (e.g., per 5 minuteintervals) Device CPU utilization (e.g., per 5 minute intervals) Packets(e.g., Octets Received/Transmitted) Device discards/errors (totals andpercentages) Port level Number of unicast/multicast/broadcast packetsper physical interface transmitted/received Number ofunicast/multicast/broadcast packets dropped per physical interfacetransmitted/received Number of bytes/octets per physical interfaceTransmitted/ Received Number of dropped bytes errors/discards perphysical interface Transmitted/Received Percentage of packetsdropped/discards per physical interface Loss of signal count Low opticalpower receive/transmit Ethernet frames receive/transmit Ethernet frameerrors received/transmitted Internal MAC error received/transmittedPause frame count received/transmitted VLAN Number ofunicast/multicast/broadcast packets per VLAN per level interfaceTransmitted/Received Number of unicast/multicast/broadcast packetsdropped per VLAN per interface transmitted/received Number ofbytes/octets per VLAN per interface Transmitted/ Received Number ofbytes/octets dropped/discards per VLAN per interfacetransmitted/received Percentage of packet dropped/discards per VLAN perinterface Ga/Gz/Gy Number of timeouts for each OCS/OFCS VLAN Number ofretries for each OCS/OFCS levels Number of errors for each OCS/OFCSAverage latency on Gy for each OCS Average latency on Ga/Gz for eachOFCS QoS level Number of unicast/multicast/broadcast packets per QoS(per (DSCP markings) transmitted/received VLAN/ Number ofunicast/multicast/broadcast packets dropped per Port) QoStransmitted/received Number of bytes/octets per QoS transmitted/receivedNumber of bytes/octets dropped/discards per QoS Transmitted/ReceivedPercentage of packets dropped/discards per QoS APN level Number ofunicast/multicast/broadcast packets per APN (transmitted/received)Number of unicast/multicast/broadcast packets dropped per APN(transmitted/received) Number of bytes/octets per APN(transmitted/received) Number of bytes/octets dropped/discards per APN(transmitted/received) Percentage of packets dropped/discards per APNNumber of active EPS bearers per APN Number of EPS bearer activationsper APN Number of EPS bearer activation failures per APN Number of EPSbearer deactivations per APN Number of PGW initiated EPS bearerdeactivations per APN Number of GTP-C messages received per APN Numberof GTP-C messages received with errors per APN

In one embodiment, the data may then be tracked for dynamicallymonitoring trends for each VLAN, port and/or interface. For example, thenetwork monitoring module may dynamically project the trends for eachVLAN, port and/or interface using a pre-determined functionality metricof each VLAN, port or interface versus utilization.

In one embodiment, the functionality metric comprises one or more of: apacket delay functionality, a packet delay over a pre-determinedthreshold functionality, a throughput functionality, a latencyfunctionality, a slow response functionality, etc.

In one embodiment, utilization refers to a ratio of a measured number ofpackets transmitted and/or received by a network component to a maximumnumber of packets the network component is designed to transmit and/orreceive. In one example, an interface may be designed totransmit/receive n1 packets per a given time period and the measurednumber of packets for the time period may by n2 packets. The utilizationfor the interface is then defined as n2/n1. In another example, a VLANport may be designed to transmit/receive n1 packets per a given timeperiod and the measured number of packets for the time period may by n2packets. The utilization for the VLAN port is then defined as n2/n1.

In order to more clearly describe the current method, the relationships:between VLAN port utilization and the packet delay functionality; andbetween VLAN port utilization and the probability of packet delay overthe pre-determined threshold functionality are first described.

First, let the packet delay functionality be represented by D and theport utilization be represented by x. In one embodiment, the aboverelationships are described with all traffic receiving the same prioritytreatment. In another embodiment, the relationships take into account aplurality of priority levels. The plurality of priority levels enablesthe service provider to offer transport prioritization based on theservice provider's quality of service offerings.

In one embodiment, the LTE network may then use a Quality of serviceClass Identifier (QCI) in conjunction with an Allocation and RetentionPriority (ARP) to create an interactive traffic class with the pluralityof priority levels. The ARP contains information about the prioritylevel of packets (e.g., a scalar with range of values 1-15), apreemption capability flag, and a preemption vulnerability flag. The ARPenables the service provider to determine whether a bearerestablishment/modification request can be accepted or needs to berejected due to a resource limitation. Table-6 provides an illustrativeARP that provides a priority level for packets of a service.

TABLE 6 An exemplary ARP ARP Priority Value Packets for Service Type 1Reserved for serving network 2 DPS/GETS (priority 1 subscriber generaldata/IMS signaling/voice traffic) 3 DPS/GETS (priority 2 subscribergeneral data/IMS signaling/voice traffic and priority 1 subscriber othertraffic) 4 DPS/GETS (priority 3 subscriber general data/IMSsignaling/voice traffic and priority 2 subscriber other traffic) 5DPS/GETS (priority 4 subscriber general data/IMS signaling/voice trafficand priority 3 subscriber other traffic) 6 DPS/GETS (priority 5subscriber general data/IMS signaling/voice traffic and priority 4 and 5subscriber other traffic) 7 E911 8 Reserved for serving network 9Reserve for future use (e.g., premium subscriber general data/IMSsignaling traffic) 10 Regular subscriber general data/IMS signalingtraffic 11 Regular subscriber GBR voice traffic 12 Regular subscriberGBR other traffic 13 Reserve for future use 14 Reserve for future use 15Low priority user (e.g., fair share) data traffic

It should be noted that the APN assignments provided in Table-6illustrates certain APN assignment strategies of the service provider.As such, the APN assignment for a service may be modified by the serviceprovider as needed and is not limited by the assignments as illustratedin Table 6.

In one embodiment, the preemption capability flag of the APR may then beused to determine which traffic may be dropped when a resourcelimitation is detected. For example, assume a service provider offerstwo priority levels: a higher priority traffic, also referred to as atype 1 traffic; and a lower priority traffic, also referred to as a type2 traffic. It should be noted that additional priority levels are withinthe scope of the present disclosure.

In one embodiment, the higher priority traffic has an absolute priorityover the lower priority traffic. When the higher priority traffic has anabsolute priority over the lower priority traffic, if type 1 trafficarrives while a server is serving a type 2 traffic, the type 1 trafficwill preempt the type 2 traffic. Namely, the server will service thetype 1 traffic immediately. The server will resume serving the type 2traffic if and when there is no more type 1 traffic to be served. Thepreemption rule applied when the higher priority traffic has an absolutepriority over the lower priority traffic is also referred to as apreemptive-resume priority rule.

In one embodiment, the higher priority traffic has priority over thelower priority traffic only for serving newly arriving traffic, whilenot allowing the higher priority traffic to interrupt the lower prioritytraffic that is already being served. For example, new traffic bearersof type 1 are served before new traffic bearers of type 2. However, newtraffic bearers of type 1 are served after existing (already beingserved) traffic bearers of type 2. The rule applied when the higherpriority traffic is not allowed to interrupt existing lower prioritybearer traffic and is also referred to as non-preemptive-resume priorityrule.

Returning to the model, the delay experienced by a packet depends on thepriority level associated with the packet and the type of priority ruleapplied when resource limitations are detected. In one example, if thepacket is for a type 1 traffic and the preemptive-resume priority ruleis applied, then the packet may experience a minimal delay. In anotherexample, if the packet is for a type 2 traffic and the preemptive-resumepriority rule is applied, the packet may experience an additional delaydue the server interrupting the type 2 traffic in order to serve a type1 traffic. Thus, the above relationships: between the packet delay andthe VLAN port utilization, and the probability of packet delay over thepre-determined threshold and the VLAN port utilization depend on whetherthe preemptive-resume priority rule is applied or thenon-preemptive-resume priority rule is applied.

Then, let the delay for the higher priority type of traffic berepresented by D1 and the port utilization for the higher prioritytraffic be represented by x1. Similarly, let the delay for the lowerpriority type of traffic be represented by D2 and the port utilizationfor the lower priority traffic be represented by x2. In addition, let a1and a2 represent parameters for a mathematical model that relates thepacket delay to the port utilization for the higher priority traffic,and let a3 and a4 represent parameters for a mathematical model thatrelates the packet delay to the port utilization for the lower prioritytraffic. In one embodiment, the mathematical model assumes the maximumport utilization is known. Without loss of generality, the known maximumutilization may then be set to 1. Moreover, the model assumes that theport utilizations x1 and x2 can be measured and 1−x1−x2>0.

Then, if the preemptive-resume priority rule is applied, the model forthe packet delay for the higher priority traffic is given by:

${D\; 1} = {{a\; 1} + {\frac{a\; 2}{\left( {1 - {x\; 1}} \right)}.}}$

The parameters a1 and a2 have constant values. In one embodiment, theparameter a1 has a constant value that represents the minimum value ofthe packet delay for the first type of traffic (the higher prioritytraffic). The minimum value of the packet delay, a1, comprisespropagation delay, processing delay by LTE equipment, routing delay andprotocol processing delay. The term a2/(1−x1) describes the relationshipbetween the packet delay due to queuing for sending the higher prioritypackets over a backhaul network and the port utilization, assuming anM/M/1 queuing model.

The values of the parameters a1 and a2 are determined from observedpacket delay data and utilization levels that correspond to the observedpacket delay data. For example, the observed packet delays for thehigher priority traffic may be represented by: D1(1), D1(2), . . . ,D1(N). The utilization levels that correspond to the observed packetdelays may be represented by: x1(1), x1(2), . . . , x1(N).

Similarly, if the preemptive-resume priority rule is applied, the modelfor the packet delay for the lower priority traffic is given by:

${D\; 2} = {{a\; 3} + {\frac{a\; 4}{\left( {1 - {x\; 1}} \right)\left( {1 - {x\; 1} - {x\; 2}} \right)}.}}$

The parameters a3 and a4 have constant values. The parameter a3 has aconstant value that represents the minimum value of the packet delay forthe second type of traffic (the lower priority traffic). The minimumvalue of the packet delay, a3, comprises propagation delay, processingdelay by LTE equipment, routing delay and protocol processing delay. Theterm

$\frac{a\; 4}{\left( {1 - {x\; 1}} \right)\left( {1 - {x\; 1} - {x\; 2}} \right)}$

describes the relationship between the packet delay due to queuing forsending the lower priority packets over a backhaul network and the portutilization, assuming an M/M/1 queuing model.

The values of the parameters a3 and a4 are determined from observedpacket delay data and utilization levels that correspond to the observedpacket delay data. For example, the observed packet delays for the lowerpriority traffic may be represented by: D2(1), D2(2), . . . , D2(N). Theutilization levels that correspond to the observed packet delays may berepresented by: x2(1), x2(2), . . . , x2(N).

In one embodiment, the values of a1, a2, a3 and a4 may be determined byminimizing the value of an objective function for best fit. It should benoted that the above functions are all convex and therefore can beoptimized separately.

In one embodiment, an L1-norm is used for finding the values of a1, a2,a3 and a4 that minimize the observation noise. For example, if thepreemptive-resume priority rule is applied, to solve for a1 and a2, theL1-norm objective function may be defined as:

$\sum\limits_{{n = 1},\; \ldots \;,N}{{{{D\; 1(n)} - \left( {{a\; 1} + {a\; 2\frac{1}{1 - {x\; 1(n)}}}} \right)}}.}$

Then, the values of a1 and a2 that minimize the summation aredetermined. Similarly, to solve for a3 and a4, the L1-norm objectivefunction may be defined as:

$\sum\limits_{{n = 1},\; \ldots \;,N}{{{{D\; 2(n)} - \left( {{a\; 3} + {a\; 4\frac{1}{\left( {1 - {x\; 1(n)}} \right)*\left( {1 - {x\; 1(n)} - {x\; 2(n)}} \right)}}} \right)}}.}$

Then, the values of a3 and a4 that minimize the summation aredetermined.

Similarly, if the non-preemptive-resume priority rule is applied, themodel for the packet delay for the higher priority traffic is given by:

${D\; 1} = {{a\; 1} + {\frac{a\; 2*\left( {1 + {x\; 2}} \right)}{\left( {1 - {x\; 1}} \right)}.}}$

The parameters a1 and a2 have constant values. The parameter a1 has aconstant value that represents the minimum value of the packet delay forthe first type of traffic (the higher priority traffic). The minimumvalue of the packet delay, a1, comprises propagation delay, processingdelay by LTE equipment, routing delay and protocol processing delay. Theterm

$\frac{a\; 2*\left( {1 + {x\; 2}} \right)}{\left( {1 - {x\; 1}} \right)}$

describes the relationship between the packet delay due to queuing forsending the higher priority packets over a backhaul network and the portutilization, assuming an M/M/1 queuing model.

The values of the parameters a1 and a2 are determined from observedpacket delay data and utilization levels that correspond to the observedpacket delay data. For example, the observed packet delays for thehigher priority traffic may be represented by: D1(1), D1(2), . . . ,D1(N). The utilization levels that correspond to the observed packetdelays may be represented by: x1(1), x1(2), . . . , x1(N).

Similarly, if the non-preemptive-resume priority rule is applied, themodel for the packet delay for the lower priority traffic is given by:

${D\; 2} = {{a\; 3} + {\frac{a\; 4*\left( {1 - {x\; 1*\left( {1 - {x\; 1} - {x\; 2}} \right)}} \right)}{\left( {1 - {x\; 1}} \right)\left( {1 - {x\; 1} - {x\; 2}} \right)}.}}$

The parameters a3 and a4 have constant values. The parameter a3 has aconstant value that represents the minimum value of the packet delay forthe second type of traffic (the lower priority traffic). The minimumvalue of the packet delay, a3, comprises propagation delay, processingdelay by LTE equipment, routing delay and protocol processing delay. Theterm

$\frac{a\; 4*\left( {1 - {x\; 1*\left( {1 - {x\; 1} - {x\; 2}} \right)}} \right)}{\left( {1 - {x\; 1}} \right)\left( {1 - {x\; 1} - {x\; 2}} \right)}$

describes the relationship between the packet delay due to queuing forsending the lower priority packets over a backhaul network and the portutilization, assuming an M/M/1 queuing model.

The values of the parameters a3 and a4 are determined from observedpacket delay data and utilization levels that correspond to the observedpacket delay data. For example, the observed packet delays for the lowerpriority traffic may be represented by: D2(1), D2(2), . . . , D2(N). Theutilization levels that correspond to the observed packet delays may berepresented by: x2(1), x2(2), . . . , x2(N).

In one embodiment, the values of a1, a2, a3 and a4 may be determined byminimizing the value of an objective function for best fit.

In one embodiment, if the non-preemptive-resume priority rule isapplied, an L1-norm is used for finding the values of a1, a2, a3 and a4that minimize the observation noise. For example, to solve for a1 anda2, the L1-norm objective function may be defined as:

$\sum\limits_{{n = 1},\; \ldots \;,N}{{{{D\; 1(n)} - \left( {{a\; 1} + {a\; 2\frac{1 + {x\; 2(n)}}{1 - {x\; 1(n)}}}} \right)}}.}$

Then, the values of a1 and a2 that minimize the summation aredetermined.

Similarly, to solve for a3 and a4, if the non-preemptive-resume priorityrule is applied, the L1-norm objective function may be defined as:

$\sum\limits_{{n = 1},\; \ldots \;,N}{{{{D\; 2(n)} - \left( {{a\; 3} + {a\; 4\frac{1 - {x\; 1(n)*\left( {1 - {x\; 1(n)} - {x\; 2(n)}} \right)}}{\left( {1 - {x\; 1(n)}} \right)*\left( {1 - {x\; 1(n)} - {x\; 2(n)}} \right)}}} \right)}}.}$

Then, the values of a3 and a4 that minimize the summation aredetermined.

Note that an L2-norm and/or other objective functions may be used.Furthermore, a commercial optimization solver may be used. As such, thepresent method may be used in conjunction with one or more optimizationtools and other objective functions.

Similarly, the relationship between the port utilization and theprobability of packet delay over the pre-determined threshold may bemathematically modeled.

First, let the probability of packet delay over the pre-determinedthreshold functionality be represented by P and the port utilization berepresented by x. In addition, assume a5 and a6 represent parameters fora mathematical model that relates the probability of packet delay overthe pre-determined threshold to the port utilization.

Then, the model for the probability of packet delay over thepre-determined threshold is given by: P=1/(1+exp(a5*x+a6)). Theparameters a5 and a6 have constant values.

The values of the parameters a5 and a6 are determined from observed dataof the probability of packet delay over the pre-determined thresholddata and observed port utilization levels that correspond to theobserved data of the probability of packet delay over the pre-determinedthreshold.

For example, for the above higher priority traffic, wherein thepreemptive-resume priority rule is applied, the observed probabilitiesof packet delay over the pre-determined threshold may be represented by:P1(1), P1(2), . . . , P1(N). The utilization levels that correspond tothe observed packet delays may be represented by: x1(1), x1(2), . . . ,x1(N).

In one embodiment, the values of a5 and a6 may be determined bymaximizing the value of an objective function for best model fitting. Inone embodiment, the objective function to be maximized is defined as:

${\sum\limits_{{n = 1},\; {\ldots \; N}}{P\; 1(n)*\log \frac{1}{1 + {\exp \left( {{a\; 5*x\; 1(n)} + {a\; 6}} \right)}}}} + {\left( {1 - {P\; 1(n)}} \right)*\log {\frac{{\exp \left( {{a\; 5*x\; 1(n)} + {a\; 6}} \right)}\;}{1 + {\exp \left( {{a\; 5*x\; 1(n)} + {a\; 6}} \right)}}.}}$

Then, the values of a5 and a6 that maximize the above objective functionare determined. For the higher priority traffic, using the values of theparameters a1 and a2, the method may project a trend for the packetdelay functionality versus the VLAN port utilization. Using the valuesof the parameters a5 and a6, the method may also project a trend for theprobability of packet delay over the pre-determined threshold versus theVLAN port utilization.

Similarly, a projection of a trend may be provided for each of thefunctionalities versus the port utilization for each VLAN and/orinterface. For example, for a specific VLAN, a port utilization level ofa specific level, e.g., 0.8, may be associated with: the probability ofa higher priority packet being dropped reaching 0.5; the mean latency ofthe higher priority packets reaching 5 ms; and the probability of ahigher priority packet being slowed down exceeding 10% reaching 0.15.(i.e., P1(slowdown>0.1)=0.15). Similarly, the utilization level ofinterfaces may be associated with specific levels of functionalities interms of latency, packet delay, etc.

The projected trends of the above functionalities for each VLAN and/orinterface may then be used to identify locations of potentialcongestions (bottlenecks). For example, a particular VLAN and/orinterface in the network may be reaching a port utilization thresholdthat is associated with a cut-off point for one or more of the abovefunctionalities. For example, if a latency of n milliseconds isunacceptable, and the port utilization level of 0.9 for an interface isassociated with a mean latency of n milliseconds, the method identifiespotential congestion for the interface as the port utilization of theinterface approaches 0.9. Note that the interface may be performing atacceptable levels in terms of other functionalities, e.g., throughput.Thus, the potential congestion may be detected for the interface basedon reaching a port utilization level that affects one or more of the keyfunctionalities.

The network monitoring module may then project the trends of thefunctionalities and identify potential congestions (bottlenecks). If thepotential congestion is detected, the network monitoring module notifiesa rule management module of the congestion.

It is important to note that the rule management module may be notifiedof other network trouble events, e.g., events other than potentialcongestion events. Therefore, in one embodiment, the rule managementmodule needs to first verify whether a reported potential congestion isdue to congestion or another event that manifests itself in a similarmanner. For example, congestions, VLAN configuration errors, othernetwork events, etc. may all have similar manifestation from theperspective of the network monitoring module. The received potentialcongestion notification needs to be analyzed to verify whether a realcongestion actually exists. The rule management module may then initiatetrouble isolation to determine if the received report of a potentialcongestion from the network monitoring module is due to a network event,an incorrect VLAN configuration, a mismatch between a quality of serviceand a class of service, or an actual congestion (bottleneck).

In one embodiment, if the rule management module determines that thereported potential congestion is actually not due to congestion, themethod proceeds to a particular process that handles the particularnetwork event. For example, the reported potential congestion may inactuality be due to a network failure event, an incorrect VLANconfiguration or a mismatch between a quality of service and a class ofservice. The method may then proceed to the respective pertinent processthat handles the particular network failure event, re-configuration ofthe VLAN, configurations of the quality of service and the class ofservice, etc. If the rule management module verifies that the reportedpotential congestion is due to a congestion (i.e., not due to anothernetwork trouble that manifests itself similarly), the method proceeds toa root-cause analysis.

An interface or VLAN congestion may be caused due to a number ofreasons. A root-cause analysis may then be performed to identify thereason for the congestion. For example, the congestion may be caused byone or more of:

-   -   A higher utilization level of buffers in network routers due to        an increase in a number of long distance high-speed connections;    -   An increase in usage of applications that generate bursty        traffic;    -   A mismatch of link speeds in a network topology;    -   A lack of appropriate congestion control mechanism in network        protocols, e.g., lack of border gateway protocol (BGP); and    -   An increase in the number of applications and/or their        respective bandwidth requirements over the internet.

In one embodiment, if the congestion is due to a higher utilizationlevel of buffers in network routers due to: an increase in a number oflong distance high-speed connections; a mismatch of link speeds in anetwork topology; or a lack of appropriate congestion control mechanismin network protocols, the method will notify a service optimizationmodule. For example, the rule management module reports the result ofthe root-cause analysis to the service optimization module. The serviceoptimization module may use the results of the root-cause analysis totake a corrective action that improves the utilization. For example, theservice optimization module may correct the detected mismatch or toimplement the appropriate congestion control mechanism such that theutilization level improves. In one embodiment, the service optimizationmodule may also report the results of the root-cause analysis to a workcenter and/or customer.

In one embodiment, if the congestion is due to an increase in usage ofapplications that generate bursty traffic or an increase in the numberof applications and/or their respective bandwidth requirements over theinternet, the method proceeds to trigger congestion control for theaffected VLAN. For example, the rule management module may send an alarmto the service optimization module when the result of the root-causeanalysis indicates that a particular VLAN is congested due to anincrease in usage. The service optimization module may check ifadditional performance monitoring data for a particular VLAN has crosseda threshold for congestion. For example, if a particular VLAN isoverloaded, the VLAN may have a slow response, or packets may be droppedat a higher rate than normal, etc. In one embodiment, the serviceoptimization module may then trigger a VLAN congestion control for theparticular VLAN. In one embodiment, the triggering of the congestioncontrol may re-direct traffic from the congested VLAN (e.g., a congestedprimary VLAN) to a secondary VLAN or other VLAN.

For example, a primary VLAN and a secondary VLAN may be configuredbetween a SIAD and an MSN. A VLAN may be overloaded, optimally loaded orunder loaded. If the primary VLAN is overloaded based on the projectedtrending as described above, the service optimization module mayredirect newly arriving lower priority traffic to the backup VLAN.

If the primary VLAN is optimally loaded, the method maintains thecongestion control level. For example, the service optimization moduletakes no action to redirect traffic to another VLAN. If the primary VLANis under loaded, the service optimization module will direct newlyarriving traffic to the primary VLAN. For example, the primary VLAN maybe able to handle more traffic than currently being offered.

If both the primary VLAN and the secondary VLAN are overloaded, theservice optimization module needs to take one or more other actions toincrease VLAN port utilization levels. For example, the method mayimplement a quality of service policy change.

In one embodiment, the redirection of traffic may be performeddynamically. In one embodiment, the redirection of traffic is performedby re-configuring VLAN identification (VLAN ID) assignments.

In one embodiment, the triggering of congestion control may be based onmean values for each of the functionalities. For example, mean latency,mean number of packets dropped, etc. In another embodiment, thetriggering of congestion control may be based on maximum values for eachof the functionalities, e.g., maximum latency, maximum number of packetsdropped, etc. The service provider may selectively determine the desiredstatistical behavior.

In one embodiment, the port utilization threshold for triggering ofcongestion control may be set for each interface. In one embodiment, theport utilization threshold for triggering of congestion control may beset for a group of interfaces. In one embodiment, the port utilizationthreshold for triggering of congestion control for a specific interfacemay be determined based on a service level agreement between the networkservice provider and the subscriber (e.g., a customer).

FIG. 2 illustrates a flow chart of a method 200 for providing congestionmanagement for a wireless network, e.g., an LTE network of the presentdisclosure. For example, one or more steps of method 200 can beimplemented by the congestion control system 104. Method 200 starts instep 205 and proceeds to step 210.

In step 210, method 200 dynamically gathers data to be used to detectthe potential congestion for an interface, a port and/or a VLAN. Forexample, a network monitoring module of a congestion control system maygather performance monitoring data from one or more eUTRAN and EPCnetwork elements in near real time or on a delayed manner, e.g., every15 minutes, every hour, every two hours and so on.

In step 220, the method may project trends for each interface, portand/or VLAN using a pre-determined functionality metric of eachinterface, port and/or VLAN. Each of the functionality metric versusutilization is tracked. For example, a network monitoring module maytrack packet delay versus interface utilization, packet delay versusport utilization, throughput versus interface utilization, and so on.For each functionality, a projection of a trend of the functionalityversus the utilization may then be provided.

In one embodiment, the functionality metric comprises one or more of: apacket delay functionality metric, a packet delay over a pre-determinedthreshold functionality metric, a throughput functionality metric, alatency functionality metric, a slow response functionality metric, andthe like.

In step 230, method 200 determines, for each interface, port and/orVLAN, if there is a potential congestion in accordance with theprojected trends of the above functionality metrics. For example, thenetwork monitoring module may identify a potential congestion for aparticular interface, port or VLAN by determining if the respectiveutilization level of the interface, port or VLAN has reached or exceededa utilization threshold that is associated with an un-acceptable levelof performance for at least one of the above functionality metrics. Forexample, a particular interface, port or VLAN in the network may bereaching a utilization threshold that is associated with a cut-off pointfor the packet delay functionality metric. If a potential congestion isdetected for an interface, a port and/or a VLAN, the network monitoringmodule proceeds to step 240. Otherwise, the method proceeds to step 210to continue gathering data.

In step 240, method 200 provides a notification of the potentialcongestion. For example, the network monitoring module notifies the rulemanagement module that a particular interface, port and/or VLAN ispotentially reaching a utilization level that is associated with anun-acceptable level of performance in terms of one or more of the abovefunctionality metrics.

In step 250, method 200 determines whether the potential congestion isdue to an actual congestion, e.g., by performing trouble isolation toverify if the received notification of a potential congestion is due toan actual congestion condition. For example, the rule management modulemay initiate a trouble isolation method to determine if the receivednotification (or report) from the network monitoring module is due to anetwork event (e.g., a network failure event), an incorrect VLANconfiguration, a mismatch between a quality of service and a class ofservice, or a congestion (i.e., bottleneck). If the method verifies thatthe received notification is due to an actual congestion condition, themethod proceeds to step 270. If the method verifies that the receivednotification is in reality due to another network trouble (i.e., anon-congestion related problem) that manifests itself in a similarmanner as a congestion condition, the method proceeds to step 260. Forexample, if the rule management module determines that the reportedtrouble is due to a network event, an incorrect VLAN configuration or amismatch between a quality of service and a class of service, the methodproceeds to step 260.

In step 260, method 200 performs the “normal” or pertinent process thathandles the particular network event, e.g., re-configuring the VLAN,setting the configuration of the quality of service and the class ofservice, etc. The method proceeds to step 210 to continue gatheringdata.

In step 270, method 200 identifies a cause for the congestion byperforming a root-cause analysis by a service type and a traffic type.For example, the interface, port and/or VLAN congestion may be causeddue to a number of reasons. The root-cause analysis may then beperformed to identify a particular reason for the congestion based onthe type of service and the type of traffic.

For example, the congestion may be caused by: a higher utilization levelof buffers in network routers due to an increase in a number of longdistance high-speed connections; an increase in usage of applicationsthat generate bursty traffic; a mismatch of link speeds in a networktopology; a lack of appropriate congestion control mechanism in networkprotocols, e.g., lack of border gateway protocol (BGP); and an increasein the number of applications and/or their respective bandwidthrequirements over the internet.

In step 275, method 200 determines if the congestion is due to anincrease in usage. For example, the congestion may be due to an increasein usage of applications that generate bursty traffic, an increase inthe number of applications, or an increase in bandwidth requirements ofapplications. If the congestion is due to an increase in usage, themethod proceeds to step 290. Otherwise, the method proceeds to step 280.

In step 280, method 200 provides a notification to invoke serviceoptimization or re-optimization. For example, the congestion may be dueto a higher utilization level of buffers in network routers due to: anincrease in a number of long distance high-speed connections; a mismatchof link speeds in a network topology; or a lack of appropriatecongestion control mechanism in network protocols. The rule managementmodule may then notify a service optimization module of the result ofthe root-cause analysis. The method then proceeds to step 285.

In optional step 285, method 200 may then re-optimize the service and/orreport the result of the root-cause analysis to a work center and/orcustomer. For example, the service optimization module may modify aquality of service, modify network topology, etc., correct a mismatch,and/or report the result of the root-cause analysis to the work centerand/or customer. The method then proceeds to either step 299 to endprocessing of the current data or return to step 210 to continuegathering data.

In step 290, method 200 triggers a congestion control. For example, aprimary VLAN and a secondary VLAN may be configured between a SIAD andan MSN. If the primary VLAN is congested and the secondary VLAN is notcongested based on the projected trending described above, the methodmay trigger a congestion control for the primary VLAN. In anotherexample, a non-preemptive-resume priority rule may be applied by aservice optimization module. For example, the congestion control maythen be performed by the service optimization module by redirectingnewly arriving lower priority traffic to the secondary (backup) VLAN,while allowing newly arriving higher priority traffic to be served bythe primary VLAN. In yet another example, a preemptive-resume priorityrule may be applied by allowing newly arriving higher priority trafficto preempt lower priority traffic that was already being served. Adetailed discussion is provided below to further disclose variouscongestion control methods. The method then proceeds to either step 299to end processing the current data or return to step 210 to continuegathering data.

In one embodiment, when the congestion control for the VLAN is triggeredin step 290, traffic is directed to the VLAN in accordance with theutilization levels of the VLAN itself and the condition of the backupVLAN. One method for directing traffic to the VLAN is illustrated belowin FIG. 3.

It should be noted that if the primary VLAN is optimally loaded, noaction is taken to redirect traffic to the secondary VLAN and newlyarriving traffic continues to be directed to the primary VLAN.Furthermore, the re-direction of traffic from the primary VLAN to thesecondary VLAN reduces the congestion if both VLANs are notsimultaneously overloaded. In the event that both the primary VLAN andthe secondary VLAN are overloaded, the service optimization module mayneed to take one or more other actions to improve VLAN utilizationlevels. For example, traffic can be redirected to yet another VALN andso on. In another example, the method may need to implement a quality ofservice policy change. The policy change may affect the Quality ofservice Class Identifier (QCI) and the Allocation and Retention Priority(ARP).

In one embodiment, the redirection of traffic is performed dynamically.In one embodiment, the redirection of traffic is performed byre-configuring VLAN identification (VLAN ID) assignments. For example,traffic from a selected list of SIADs, from a selected list of physicalinterfaces on SIADs, from a selected list of logical interfacessupported by the congested primary VLAN, or combinations thereof, may bedirected to the secondary VLAN.

In one embodiment, the redirection of traffic continues until autilization threshold for returning traffic to the primary VLAN isreached. For example, the service provider may set a second utilizationthreshold, wherein the second utilization threshold is associated withnormal conditions for all tracked functionality metrics. For example,the second utilization threshold may be a utilization level thatindicates that all functionality metric, e.g., the packet delayfunctionality metric, the packet delay over the pre-determined thresholdfunctionality metric, the throughput functionality metric, etc. arenormal.

In one embodiment, the service optimization module performs thecongestion control using an algorithm that tracks overloads of VLANs(primary and secondary), directs traffic to one of the VLANs inaccordance with the overload conditions on the VLANs, and takes otheractions if the VLAN congestion control algorithm cannot be invoked dueto congestion on both the primary and backup VLANs. It should be notedthat additional VLANs greater than two (primary and secondary) can beemployed.

FIG. 3 illustrates a flow chart of a method 300 for directing traffic toa primary VLAN of the present disclosure using a utilization level. Asdescribed above, method 200 may trigger a congestion control, ifnecessary. In one embodiment, the traffic is directed to the primaryVLAN or the backup of the primary VLAN (the secondary VLAN) based oncongestion conditions and utilization levels of the primary andsecondary VLANs. The triggering of the congestion control then operatesin conjunction with a method that directs traffic. For example, one ormore steps of the method 300 for directing traffic can be implemented bya service optimization module. Method 300 starts in step 305 andproceeds to step 310.

In step 310, method 300 determines if a primary VLAN is overloaded. Forexample, a particular primary VLAN may be operating with a utilizationlevel above a pre-determined threshold. For example, a utilization levelof 0.8, 0.9, etc. may be set as the pre-determined threshold. It shouldbe noted that the present disclosure is not limited by a particularthreshold value. If the primary VLAN is overloaded, the method proceedsto step 330. Otherwise, the method proceeds to step 320.

In step 320, method 300 maintains the current utilization level. Forexample, the method makes no changes to the current VLAN ID assignmentssuch that the physical and logical interfaces supported by the primaryVLAN continue to direct traffic to the primary VLAN. The method thenproceeds to step 310.

In step 330, method 300 determines if a backup (secondary) VLAN isoverloaded. For example, the secondary VLAN may be serving as a backupVLAN to the overloaded primary VLAN. If the secondary VLAN isoverloaded, the method proceeds to step 340. Otherwise, the methodproceeds to step 350.

In step 340, method 300 makes changes to the quality of serviceassociated with the provided services (e.g., dropping packets, queuingpackets) and/or takes other actions (adding more hardware or physicalresources to support the VLANs), wherein the other actions are intendedto improve the utilization levels of the primary VLAN and the secondaryVLAN. The method then proceeds to step 310.

In step 350, method 300 directs newly arriving traffic to the secondaryVLAN. For example, newly arriving low priority traffic may be directedto the secondary VLAN by re-configuring the pertinent VLAN IDassignments.

In step 360, method 300 determines if the secondary VLAN is overloaded.For example, the secondary VLAN may become overloaded over time. If thesecondary VLAN is overloaded, the method proceeds to step 340. Otherwisethe method proceeds to step 370.

In step 370, method 300 determines if the utilization level of theprimary VLAN has reached a threshold for resuming directing of trafficback to the primary VLAN. For example, if the utilization level dropsfrom a level that indicated congestion (e.g., a utilization level of0.8) to a level that indicates that the primary VLAN is under-loaded(e.g., a utilization level of 0.5), the method determines that trafficmay now be directed to the primary VLAN. For example, the VLAN IDassignments may be re-configured such that the primary VLAN is beingused instead of the secondary (backup) VLAN. If the method determinesthat the utilization level has reached the threshold for resumingdirecting of traffic to the primary VLAN, the method proceeds to step380. Otherwise, the method proceeds to step 350.

In step 380, method 300 directs newly arriving traffic to the primaryVLAN. For example, the method directs newly arriving traffic to theprimary VLAN instead of the backup VLAN. The method then proceeds tostep 310 or ends, e.g., when called by method 400 as discussed below.

FIG. 4 illustrates a flow chart of a method 400 for providing acongestion control (broadly a priority handling congestion control) forcontrolling traffic for a VLAN. As described above, method 200 maytrigger a congestion control, if necessary. In one embodiment, whencongestion exists, traffic can be managed based on whether preemption ofa lower priority traffic to serve a higher priority traffic is allowed.The triggering of the congestion control then operates in conjunctionwith a method that directs traffic in accordance with apreemptive-resume rule or a non-preemptive-resume rule that is beingapplied. For example, one or more steps of the method 400 for directingtraffic can be implemented by a service optimization module. Method 400starts in step 405 and proceeds to step 410.

In step 410, method 400 determines if a packet is received for a VLAN.For example, the method determines if a packet to be processed via acongestion control method is received. If a packet is received for theVLAN, the method proceeds to step 420. Otherwise, the method returns tostep 410.

In step 420, method 400 determines if a preemptive-resume rule is beingapplied. If the preemptive-resume rule is being applied, the methodproceeds to step 430. Otherwise the method proceeds to step 460.

In step 430, method 400 determines a priority of the traffic (or broadlydata flow) associated with the received packet. For example, the packetmay be for a higher priority traffic type (e.g., traffic type 1described above) or a lower priority traffic type (e.g., traffic type 2described above or lower if there are more types).

In one embodiment, the received traffic may have any number of prioritylevels. For example, Table-6 indicated 15 priority levels for traffic.It should be noted that the network service provider may determine anyappropriate number of priority levels to be supported. Moreover, thevarious priority levels may be mapped to any number of classes ofservice. For example, traffic from priority levels one (1) to two (2)may be mapped to a first class of service, priority levels three (3) tosix (6) may be mapped to another class of service, and so on. Thepre-emption of the current method may be performed based on any numberof mapping schemes. As such, the determination of whether a packet has ahigher priority traffic type as compared to that of another packet thathas a lower priority traffic type may be based on a priority scheme asshown in Table-6, a mapping of the priorities to classes of service, orany other type of priority mapping.

In step 435, method 400 determines if there is a lower priority trafficbeing served that may be preempted. If there is a lower priority trafficbeing served, the method proceeds to step 440. Otherwise, the methodproceeds to step 465.

In step 440, method 400 preempts the lower priority traffic and servesthe current packet immediately. The method may then return to serve thelower priority traffic and/or proceed to step 410 to continue receivingpackets. In another embodiment, the preempting of the lower prioritytraffic is performed simply by re-allocating bandwidth that waspreviously allocated to the lower priority traffic type, e.g.,allocating more bandwidth to a higher priority level and allocating lessbandwidth to a lower priority level.

For example, the higher priority traffic may have been allocated 50% ofthe bandwidth of the VLAN and the lower priority traffic may have beenallocated the remaining 50% of the bandwidth of the VLAN. Ifreallocation is required, then the preemption may then be performed byincreasing the bandwidth allocation for the higher priority traffic, andconsequently reducing the allocation for the lower priority traffic. Forinstance, the new bandwidth allocation for the VLAN may allocate 60% forthe higher priority traffic type and 40% for the lower priority traffictype, and so on.

In another example, there may be more than two levels of priority oftraffic. The preemption may then be performed by re-allocating theVLAN's bandwidth for all the priority levels, or by re-allocating forsome levels of priorities—while leaving allocations for other levels ofpriorities unchanged. The pre-emption may then be performed by firstselecting the priority level that is to be targeted for a reduction ofits bandwidth allocation. For example, if there are four prioritylevels, the highest priority type may preempt traffic of the secondhighest priority level, traffic of the third highest priority level,and/or traffic of the lowest priority level. For instance, there-allocation may be performed by allocating bandwidth that waspreviously allocated to the lowest priority level traffic, the secondhighest priority level, and/or the third highest priority level.

In step 460, method 400 determines if there is adequate capacityavailable on the VLAN for serving the packet, i.e., without preemption.If there is adequate capacity available on the VLAN for serving thepacket, the method proceeds to step 470. Otherwise, the method proceedsto step 465.

In step 470, method 400 processes or serves the packet that is receivedimmediately. For example, the method serves the new traffic becausethere is adequate capacity on the VLAN. The method then proceeds to step410.

In step 465, method 400 may trigger method 300 as discussed above. Themethod then proceeds to step 410.

Thus, the method 300 and method 400 are congestion management methodsthat can be triggered by the method 200 for providing congestionmanagement for a wireless network, e.g., an LTE network. It should benoted that methods 300 and 400 can be implemented individually or inconjunction with each other. For example, the method 300 and the method400 may be used simultaneously to consider conditions of both theprimary and secondary VLANs, and the rules that govern whether thepre-emptive-resume rule or the non-preemptive-resume rule is to beapplied during the directing of traffic to the pertinent VLAN.

It should be noted that although not explicitly specified, one or moresteps of the method 200, 300 or 400 described herein may include astoring, displaying and/or outputting step as required for a particularapplication. In other words, any data, records, fields, and/orintermediate results discussed in the method can be stored, displayed,and/or outputted to another device as required for a particularapplication. Furthermore, steps or blocks in FIG. 2, FIG. 3 or FIG. 4that recite a determining operation, or involve a decision, do notnecessarily require that both branches of the determining operation bepracticed. In other words, one of the branches of the determiningoperation can be deemed as an optional step.

FIG. 5 depicts a high level block diagram of a general purpose computersuitable for use in performing the functions described herein. Asdepicted in FIG. 5, the system 500 comprises a processor element 502(e.g., a CPU), a memory 504, e.g., random access memory (RAM) and/orread only memory (ROM), a module 505 for providing a VLAN congestioncontrol, and various input/output devices 506 (e.g., storage devices,including but not limited to, a tape drive, a floppy drive, a hard diskdrive or a compact disk drive, a receiver, a transmitter, a speaker, adisplay, a speech synthesizer, an output port, and a user input device(such as a keyboard, a keypad, a mouse, and the like)).

It should be noted that the present disclosure can be implemented insoftware and/or in a combination of software and hardware, e.g., usingapplication specific integrated circuits (ASIC), a general purposecomputer or any other hardware equivalents. In one embodiment, thepresent module or process 505 for providing a VLAN congestion controlcan be loaded into memory 504 and executed by processor 502 to implementthe functions as discussed above. As such, the present process 505 forproviding a VLAN congestion control (including associated datastructures) of the present disclosure can be stored on a non-transitory(e.g., tangible and physical) computer readable storage medium, e.g.,RAM memory, magnetic or optical drive or diskette and the like.

While various embodiments have been described above, it should beunderstood that they have been presented by way of example only, and notlimitation. Thus, the breadth and scope of a preferred embodiment shouldnot be limited by any of the above-described exemplary embodiments, butshould be defined only in accordance with the following claims and theirequivalents.

What is claimed is:
 1. A method for providing congestion management fora wireless communication network, the method comprising: projecting, viaa processor, dynamically a trend for a network element of the wirelesscommunication network, using a functionality metric associated with thenetwork element of the wireless communication network, wherein theprojecting the trend comprises projecting the trend using thefunctionality metric of the network element as a function of autilization level of the network element, wherein the functionalitymetric comprises a packet delay functionality metric, wherein theutilization level comprises a ratio between a measured number of packetstransmitted and a maximum number of packets the network element isdesigned to transmit; determining, via the processor, if there is apotential congestion in accordance with the trend, wherein the potentialcongestion is detected when the trend for the network element isapproaching a cut-off point, wherein the network element is stillperforming at an acceptable level when the potential congestion isdetected; and providing, via the processor, a notification of thepotential congestion, when there is a potential congestion for thenetwork element of the wireless communication network.
 2. The method ofclaim 1, wherein the network element comprises an interface.
 3. Themethod of claim 1, wherein the network element comprises a port.
 4. Themethod of claim 1, wherein the network element comprises a virtual localarea network.
 5. The method of claim 1, further comprising: performing atrouble isolation to determine if the notification is due to an actualcongestion condition.
 6. The method of claim 5, further comprising:identifying a cause for the actual congestion condition by performing aroot-cause analysis by a service type and a traffic type, when thetrouble isolation determined that the notification is due to the actualcongestion condition.
 7. The method of claim 6, wherein the root-causeanalysis determines if the actual congestion condition is due to anincrease in usage.
 8. The method of claim 7, further comprising:triggering a congestion control for the network element when the actualcongestion condition is due to the increase in usage.
 9. The method ofclaim 8, wherein the triggering the congestion control comprises:determining if a first virtual local area network is operating with autilization level above a first pre-determined threshold; determining ifa second virtual local area network is operating above a secondpre-determined threshold, when the first virtual local area network isoperating with the utilization level above the first pre-determinedthreshold; and directing newly arriving traffic to the second virtuallocal area network, when the second virtual local area network is notoperating with a utilization level above the second pre-determinedthreshold.
 10. The method of claim 9, further comprising: determining ifthe utilization level of the first virtual local area network reached athird pre-determined threshold, wherein the third pre-determinedthreshold is a threshold for resuming directing of traffic back to thefirst virtual local area network; and directing newly arriving trafficto the first virtual local area network, when the utilization level ofthe first virtual local area network has reached the thirdpre-determined threshold.
 11. The method of claim 1, wherein thedetermining the potential congestion is based on data gathered by anetwork service provider.
 12. The method of claim 1, wherein thefunctionality metric further comprises a latency functionality metric.13. The method of claim 8, wherein the triggering the congestion controlcomprises employing a priority handling congestion control.
 14. Atangible computer-readable medium storing a plurality of instructionswhich, when executed by a processor, cause the processor to performoperations for providing congestion management for a wirelesscommunication network, the operations comprising: projecting dynamicallya trend for a network element of the wireless communication network,using a functionality metric associated with the network element of thewireless communication network, wherein the projecting the trendcomprises projecting the trend using the functionality metric of thenetwork element as a function of a utilization level of the networkelement, wherein the functionality metric comprises a packet delayfunctionality metric, wherein the utilization level comprises a ratiobetween a measured number of packets transmitted and a maximum number ofpackets the network element is designed to transmit; determining ifthere is a potential congestion in accordance with the trend, whereinthe potential congestion is detected when the trend for the networkelement is approaching a cut-off point, wherein the network element isstill performing at an acceptable level when the potential congestion isdetected; and providing a notification of the potential congestion, whenthere is a potential congestion for the network element of the wirelesscommunication network.
 15. The tangible computer-readable medium ofclaim 14, the operations further comprising: performing a troubleisolation to determine if the notification is due to an actualcongestion condition.
 16. The tangible computer-readable medium of claim15, the operations further comprising: identifying a cause for theactual congestion condition by performing a root-cause analysis by aservice type and a traffic type, when the trouble isolation determinedthat the notification is due to the actual congestion condition.
 17. Anapparatus for providing congestion management for a wirelesscommunication network, the apparatus comprising: a processor; and acomputer readable medium storing a plurality of instructions which, whenexecuted by the processor, cause the processor to perform operations,the operations comprising: projecting dynamically a trend for a networkelement of the wireless communication network, using a functionalitymetric associated with the network element of the wireless communicationnetwork, wherein the projecting the trend comprises projecting the trendusing the functionality metric of the network element as a function of autilization level of the network element, wherein the functionalitymetric comprises a packet delay functionality metric, wherein theutilization level comprises a ratio between a measured number of packetstransmitted and a maximum number of packets the network element isdesigned to transmit; determining if there is a potential congestion inaccordance with the trend, wherein the potential congestion is detectedwhen the trend for the network element is approaching a cut-off point,wherein the network element is still performing at an acceptable levelwhen the potential congestion is detected; and providing a notificationof the potential congestion, when there is a potential congestion forthe network element of the wireless communication network.
 18. Theapparatus of claim 17, the operations further comprising: performing atrouble isolation to determine if the notification is due to an actualcongestion condition.
 19. The apparatus of claim 18, the operationsfurther comprising: identifying a cause for the actual congestioncondition by performing a root-cause analysis by a service type and atraffic type, when the trouble isolation determined that thenotification is due to the actual congestion condition.
 20. Theapparatus of claim 19, wherein the root-cause analysis determines if theactual congestion condition is due to an increase in usage.